ArticleSensors (Basel, Switzerland)2022
Hybrid Interacting Multiple Model Filtering for Improving the Reliability of Radar-Based Forward Collision Warning Systems.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 8 citations in OpenAlex.
- Object Detection, Recognition, and Tracking Algorithms for ADASs-A Study on Recent Trends.Sensors (Basel, Switzerland) · 2023Review
- Numerical Analysis of an Autonomous Emergency Braking System for Rear-End Collisions of Electric Bicycles.Sensors (Basel, Switzerland) · 2023Article
- Forward Collision Warning Strategy Based on Millimeter-Wave Radar and Visual Fusion.Sensors (Basel, Switzerland) · 2023Article
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Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Automotive forward collision warning (FCW) systems based on radar sensors attracted widespread attention in recent years. To achieve a reliable FCW, it is essential to accurately estimate the position and velocity of a preceding vehicle. To this end, this study proposed a novel estimation algorithm, which is a hybrid of interacting multiple model probabilistic data association (IMM-PDA) and finite impulse response (FIR) filters. Although the IMM-PDA filter is one of the most successful algorithm for tracking a maneuvering target in clutters, it sometimes exhibits divergence owing to modeling errors. In this study, the divergent IMM-PDA filter in the novel algorithm was reset and recovered using an assisting FIR filter. Consequently, this enabled reliable estimation for FCW. The improved reliability of the proposed algorithm was demonstrated through the simulation of preceding vehicle tracking using automotive radars.
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Registered trials
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